What actually happens to a metric between the moment your application emits it and the moment a retention policy deletes it? In this talk, we deconstruct a metric’s life and learn about the magic tricks that make them possible.

We cover how a metric is created with the OpenTelemetry SDK and how its *type* shapes aggregation; how its name and labels become a unique time series; how the backend absorb a firehose of writes and compress it with Gorilla-like compression; what every query engine must do (select, filter, aggregate) and why some operations are cheap and others bring a backend to its knees; and finally downsampling and retention, where the metric grows old and dies.

Every backend varies in the details, but they share the same fundamental ideas. You'll leave with a mental model of what's happening under the hood of *any* metrics system. On case of showing examples, we will focus in prometheus and prometheus ecosystem, but the intention is to focus on the common practices that are widely shared by the industry.